Python: DevUI - Internal Refactor, Conversations API support, and per… (#1235)

* Python: DevUI - Internal Refactor, Conversations API support, and performance improvements

Comprehensive refactor of DevUI package including samples relocation,
frontend reorganization, OpenAI Conversations API support, and critical
performance and code quality improvements.

Key Changes:

Architecture & Organization
- Moved DevUI samples to python/samples/getting_started/devui/
- Consolidated with other framework samples for better discoverability
- Added .env.example files and comprehensive README
- Restructured frontend components into feature-based folders (agent, workflow, gallery, layout)
- Created new OpenAI-compliant message renderers (devui should render oai responses types primarily)

New Features
- Added _conversations.py (467 lines) - Full conversation storage abstraction, replaces the /threads endpoint to better match oai conversations api
- Implements OpenAI Conversations API for thread management, Supports in-memory and extensible storage backends

API Simplification
- Use 'model' field as entity_id (agent/workflow name) instead of extra_body
- Use standard OpenAI 'conversation' field for conversation context.

Performance & Quality Improvements
- Improved context management in MessageMapper with bounded memory (~500KB max)
- Implemented hybrid LRU + cleanup approach to prevent unbounded memory growth
- General QOL improvement - Eliminated ~150 lines of dead/duplicate code, Consolidated helper functions into _utils.py, Extracted magic numbers to module-level constants, Optimized conversation item lookups with index-based approach

Testing
- Added test_conversations.py (13 tests)
- Added test_performance_fixes.py (9 tests)
- Updated existing tests for code consolidation
- 53 tests passing

Impact: 76 files changed: +4,106 insertions, -2,373 deletions
All linting and formatting checks passing. No breaking changes - backward compatible.

Migration: Samples moved to python/samples/getting_started/devui/

* readme lint fixes

* initial support for function approval and minor ui fixes

python/packages/devui/tests/capture_messages.py

@@ -10,6 +10,7 @@ import asyncio
 import contextlib
 import http.client
 import json
+import logging
 import threading
 import time
 from pathlib import Path
@@ -20,12 +21,20 @@ from openai import OpenAI
 
 from agent_framework_devui import DevServer
 
+logger = logging.getLogger(__name__)
+
 
 def start_server() -> tuple[str, Any]:
     """Start server with samples directory."""
-    # Get samples directory
+    # Get samples directory - updated path after samples were moved
     current_dir = Path(__file__).parent
-    samples_dir = current_dir.parent / "samples"
+    # Samples are now in python/samples/getting_started/devui
+    samples_dir = current_dir.parent.parent.parent / "samples" / "getting_started" / "devui"
+
+    if not samples_dir.exists():
+        raise RuntimeError(f"Samples directory not found: {samples_dir}")
+
+    logger.info(f"Using samples directory: {samples_dir}")
 
     # Create and start server with simplified parameters
     server = DevServer(
@@ -41,7 +50,7 @@ def start_server() -> tuple[str, Any]:
         app=app,
         host="127.0.0.1",
         port=8085,
-        log_level="info",  # More verbose to see tracing setup
+        # log_level="info",  # More verbose to see tracing setup
     )
     server_instance = uvicorn.Server(server_config)
 
@@ -80,10 +89,9 @@ def capture_agent_stream_with_tracing(client: OpenAI, agent_id: str, scenario: s
 
     try:
         stream = client.responses.create(
-            model="agent-framework",
+            model=agent_id,  # DevUI uses model field as entity_id
             input="Tell me about the weather in Tokyo. I want details.",
             stream=True,
-            extra_body={"entity_id": agent_id},
         )
 
         events = []
@@ -122,13 +130,12 @@ def capture_workflow_stream_with_tracing(
 
     try:
         stream = client.responses.create(
-            model="agent-framework",
+            model=workflow_id,  # DevUI uses model field as entity_id
             input=(
                 "Process this spam detection workflow with multiple emails: "
                 "'Buy now!', 'Hello mom', 'URGENT: Click here!'"
             ),
             stream=True,
-            extra_body={"entity_id": workflow_id},
         )
 
         events = []
@@ -161,70 +168,6 @@ def capture_workflow_stream_with_tracing(
         return [error_event]
 
 
-def capture_agent_with_bad_config(base_url: str, agent_id: str) -> list[dict[str, Any]]:
-    """Capture agent events with intentionally bad configuration to test error handling."""
-
-    # Test with invalid API key
-    bad_client = OpenAI(base_url=f"{base_url}/v1", api_key="invalid-api-key-123")
-
-    try:
-        return capture_agent_stream_with_tracing(bad_client, agent_id, "bad_api_key")
-    except Exception as e:
-        return [
-            {
-                "type": "error",
-                "scenario": "bad_api_key",
-                "error_message": str(e),
-                "error_type": type(e).__name__,
-                "timestamp": time.time(),
-            }
-        ]
-
-
-def capture_agent_with_wrong_model(base_url: str, agent_id: str) -> list[dict[str, Any]]:
-    """Capture agent events with wrong model name to test error handling."""
-
-    client = OpenAI(
-        base_url=f"{base_url}/v1",
-        api_key="dummy-key",  # Use the same key as success case
-    )
-
-    try:
-        stream = client.responses.create(
-            model="gpt-4-nonexistent-model",  # Wrong model name
-            input="Tell me about the weather in Tokyo. I want details.",
-            stream=True,
-            extra_body={"entity_id": agent_id},
-        )
-
-        events = []
-        for event in stream:
-            # Serialize the entire event object
-            try:
-                event_dict = json.loads(event.model_dump_json())
-            except Exception:
-                # Fallback to dict conversion if model_dump_json fails
-                event_dict = event.__dict__ if hasattr(event, "__dict__") else str(event)
-
-            events.append(event_dict)
-
-            if len(events) >= 200:
-                break
-
-        return events
-
-    except Exception as e:
-        return [
-            {
-                "type": "error",
-                "scenario": "wrong_model",
-                "error_message": str(e),
-                "error_type": type(e).__name__,
-                "timestamp": time.time(),
-            }
-        ]
-
-
 def main():
     """Main capture script - testing both success and failure scenarios."""